This article focuses on solely RStudio and R as a building block for a class that requires the use of statistical computing. The free version provides code editing tools, an integrated debugging experience, and package development tools. RStudio is an interactive development environment (IDE) available for the R language. R provides an interactive command line experience.
It's used in the statistical analysis of genetics to natural language processing to analyzing financial data. R is an open-source language used for statistical computing and graphics. For more information, see What's New in the August 2022 Update. This book helps you understand the theory that underpins ggplot2, and will help you create new types of graphics specifically tailored to your needs.This article references features available since the August 2022 Update, when lab plans replaced lab accounts. It describes the theoretical underpinnings of ggplot2 and shows you how all the pieces fit together. If you’ve mastered the basics and want to learn more, read ggplot2: Elegant Graphics for Data Analysis. It provides a set of recipes to solve common graphics problems. If you want to dive into making common graphics as quickly as possible, I recommend The R Graphics Cookbook by Winston Chang.
If you’d like to follow a webinar, try Plotting Anything with ggplot2 by Thomas Lin Pedersen. If you’d like to take an online course, try Data Visualization in R With ggplot2 by Kara Woo. R for Data Science is designed to give you a comprehensive introduction to the tidyverse, and these two chapters will get you up to speed with the essentials of ggplot2 as quickly as possible. The Data Visualisation and Graphics for communication chapters in R for Data Science. Currently, there are three good places to start: If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages.
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